Deep Dives

In this text, I'll introduce you to hierarchical Bayesian (HB) modelling, a versatile approach to mechanically mix the outcomes of multiple sub-models. This method enables estimation of individual-level effects by optimally combining information across...

Table of Contents Introduction It’s infrequently that you simply hear the Ruby language mentioned when discussing AI. Python, after all, is the king on this world, and for good reason. The community has coalesced across the language....

Scientific publication T. M. Lange, M. Gültas, A. O. Schmitt & F. Heinrich (2025). optRF: Optimising random forest stability by determining the optimal variety of trees. , 26(1), 95.Follow this LINK to the unique publication. ...

trees are a preferred supervised learning algorithm with advantages that include with the ability to be used for each regression and classification in addition to being easy to interpret. Nevertheless, decision trees aren’t...

Recent large language models (LLMs) — comparable to OpenAI’s o1/o3, DeepSeek’s R1 and Anthropic’s Claude 3.7 — display that allowing the model to think deeper and longer at test time can significantly enhance model’s...

Whether you’re preparing for interviews or constructing Machine Learning systems at your job, model compression has grow to be vital skill. Within the era of LLMs, where models are getting larger and bigger, the...

I the possibility to create an MCP server for an observability application in an effort to provide the AI agent with dynamic code evaluation capabilities. Due to its potential to rework applications, MCP is...

It’s well that  we eat matters — but what if  and  we eat matters just as much? Within the midst of ongoing scientific debate around the advantages of intermittent fasting, this query becomes much more intriguing. As someone...